C
PROJECT
“Chase River Adult
Tagging Fall 2000”
Part 1.
Peterson (Maroon)
Refer to the tagging data #1
answer the following questions:
(1)
Find the number of males and females.
(2)
Find the number of males and females broken down by size.
For that
system we define jacks (mature males that are only 1.5 years old) as
fish that are less than 370 mm fork length.
(3)
Based on sample measurements, what proportion
of males were jacks?
(4)
What was the ratio of males to females based on sampling data?
(5)
Use the Descriptive Statistics of Excel to find important statistics for the
sample. For example, find the mean, median, range and standard deviation for
the fork length of returning male adults, say RA, at Chase River?
(6)
Repeat part (5) for the fork length of the jack’s say, RJ,
returning to the Chase River?
(7)
Repeat part (5) for the fork length of returning females say, FE.
(8)
For each variable RA, RJ, and FE construct a Frequency
Distribution Histogram and Pie Chart. Comment on the shape of the
histograms of RA, RJ, and FE.
(9)
Find the mean length of all males and the mean length of females in sample
#1.
(10)
Construct a 95% confidence interval for the
mean length of RA population. Do the same for FE population
(11)
Construct a 95% confidence interval for the proportion of males in the
Maroon population.
(12)
Use 95% confidence and a 0.03 margin of error to find the sample size
necessary to estimate the proportion of jacks in adult males.
(13)
Use the sample data to establish the claim
that the mean length of all males is less than 407mm, by using mean length
less or equal to 407mm as the null hypothesis.
Part 2.
Peterson (Green)
Use the
attached tagging data #2 to answer the following questions:
(1)Use
the Descriptive Statistics of Excel to find important statistics for the
sample. For example, find the mean, median, range and standard deviation for
the fork length of returning adults RA, RJ, and FE.
(2)
Based on sample measurements, what was
proportion of adult males were jacks?
(3)
For each variable RA, RJ, and FE in part (1) construct a
Frequency Distribution Histogram and Pie Chart. Comment on the shape
of the histograms of RA, RJ, and FE.
(4)
What was the ratio of males to females based
on sampling data?
(5)
Find the mean length of all males and the mean
length of females in sample #2.
(6)
Construct a 95% confidence interval for the mean length of RA population.
(7)
Construct a 95% confidence interval for the proportion of males in the Green
population.
(8)
Use 95% confidence and a 0.03 margin of error to find the sample size
necessary to estimate the proportion of jacks in adult males.
(9)
Use the sample data to test the claim that the mean length of all males is
less or equal to 407mm.
Part 3.
Comments
&
Conclusions
(1) Compare the
results in Part 1 (4) and Part 2 (4).
(2)
Compare the results in Part 1 (8) and Part 2 (3). Do the
corresponding histograms appear to be similar each other? Explain carefully.
(3)
Compare the results in Part 1 (9) and Part 2 (5). Do the
corresponding numbers appear to be consistent with each other? Explain
carefully.
(4)
Compare the results in Part 1 (10,11) and Part 2 (6,7). Do the
corresponding confidence intervals appear to be consistent with each other?
Explain carefully
(5)
Refer to the mean length of males and females in Part 1. Do the
samples indicate that one sex significantly larger than the other in both
samples? Explain carefully. Do the same for Part 2.
(6)
Compare the results in Part 1 (3) and Part 2 (2). Do the
corresponding numbers appear to be similar each other? Explain carefully
(7)
In Part 1 (13) and Part 2 (9) you tested the claim that mean length
of all males is less than 407 mm. But we use in Part 1 sample size of 100and
size of 37 in Part 2. For these results, could there be a potential problem
due to the large number of missing values in Part 2? Explain.
(8)
Compare the results in Part 1 (11) and Part 2 (7). Do the
corresponding confidence intervals appear to be consistent with each other?
Explain carefully.
(9)
Over the years we have gathered data. Do you think we should include
more attributes into the data? What should those parameters be? In analyzing
your statistical results, can you indicate which statistics are very useful
to a marine researcher?
Explain carefully your recommendations.
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